1. Field of Invention
This invention relates to systems and methods for improving the appearance of captured images.
1. Description of Related Art
In the digital reproduction of documents, a bitmap is created which may be described as an electronic image with discrete signals, i.e. pixels, defined by a position and a density. In conventional image capture devices, such as facsimile and scanner devices, image degradation of captured bilevel image data often occurs. This degradation, such as lower resolution, noise, change in contrast and the like, is well within the visual acuity of the human eye. If the captured image data is output to a recording medium without adjusting for the degradation, the outputted image will include the degradation. Even though such bilevel images are usually readable, they are often difficult or unpleasant to read. Such images are also not presentable for formal purposes. This is because the human eye can sense this image degradation, and the perceived quality of the resulting image suffers greatly even for small degradation.
Various attempts at remedying such problems have been performed. An example is U.S. Pat. No. 5,303,313 to Mark et al., which provides a method of image enhancement through use of a compressed representative image. Another example is described in J.D. Hobby et al., “Enhancing degraded document images via bitmap clustering and averaging,” ICDAR '97: Fourth Int. Conference on Document Analysis and Recognition, 1997. Both U.S. Pat. No. 5,303,313 and the Hobby article provides a basic strategy. In Hobby, the strategy includes: clustering bitmaps, computing representatives for each cluster, and then assembling an output. For initial clustering, Hobby uses a feature-based approach. To compute cluster representatives, Hobby uses a method that aligns the scans by centroids of black pixels, sums the scans to give a histogram, smooths the histogram to give a gray-level representative, and determines a polygonal outline that stays within a certain gray “tube” yet has a minimum number of inflection points. This computation method is described in J.D. Hobby and H.S. Baird, “Degraded Character Image Restoration”, Proc. 5th Annual Symp. On Document Analysis and Image Retrieval, 1996, pps. 177–189. To align and form the assembled output, Hobby appears to use the alignment computed when computing cluster representatives. U.S. Pat. No. 5,303,313 does not perform any reclustering, and instead is concerned primarily with compression.
While the Hobby method shows some improvement in images and increases resolution, there are many refinements that can be made.